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. 2016 Jan;214(1):110.e1-9.
doi: 10.1016/j.ajog.2015.08.048. Epub 2015 Aug 28.

Geospatial analysis of food environment demonstrates associations with gestational diabetes

Maike K Kahr  1 , Melissa A Suter  1 , Jerasimos Ballas  1 , Susan M Ramin  1 , Manju Monga  1 , Wesley Lee  1 , Min Hu  1 , Cindy D Shope  1 , Arina Chesnokova  1 , Laura Krannich  1 , Emily N Griffin  1 , Joan Mastrobattista  1 , Gary A Dildy  1 , Stacy L Strehlow  1 , Ryan Ramphul  2 , Winifred J Hamilton  2 , Kjersti M Aagaard  3
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Geospatial analysis of food environment demonstrates associations with gestational diabetes

Maike K Kahr et al. Am J Obstet Gynecol. 2016 Jan.

Abstract

Background: Gestational diabetes mellitus (GDM) is one of most common complications of pregnancy, with incidence rates varying by maternal age, race/ethnicity, obesity, parity, and family history. Given its increasing prevalence in recent decades, covariant environmental and sociodemographic factors may be additional determinants of GDM occurrence.

Objective: We hypothesized that environmental risk factors, in particular measures of the food environment, may be a diabetes contributor. We employed geospatial modeling in a populous US county to characterize the association of the relative availability of fast food restaurants and supermarkets to GDM.

Study design: Utilizing a perinatal database with >4900 encoded antenatal and outcome variables inclusive of ZIP code data, 8912 consecutive pregnancies were analyzed for correlations between GDM and food environment based on countywide food permit registration data. Linkage between pregnancies and food environment was achieved on the basis of validated 5-digit ZIP code data. The prevalence of supermarkets and fast food restaurants per 100,000 inhabitants for each ZIP code were gathered from publicly available food permit sources. To independently authenticate our findings with objective data, we measured hemoglobin A1c levels as a function of geospatial distribution of food environment in a matched subset (n = 80).

Results: Residence in neighborhoods with a high prevalence of fast food restaurants (fourth quartile) was significantly associated with an increased risk of developing GDM (relative to first quartile: adjusted odds ratio, 1.63; 95% confidence interval, 1.21-2.19). In multivariate analysis, this association held true after controlling for potential confounders (P = .002). Measurement of hemoglobin A1c levels in a matched subset were significantly increased in association with residence in a ZIP code with a higher fast food/supermarket ratio (n = 80, r = 0.251 P < .05).

Conclusion: As demonstrated by geospatial analysis, a relationship of food environment and risk for gestational diabetes was identified.

Keywords: food environment; geospatial analysis; gestational diabetes; neighborhood; pregnancy outcome.

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Conflict of interest statement

Disclosure Statement: The authors report no conflicts of interest.

Figures

Figure 1
Figure 1. Geographical distribution of gestational diabetes prevalence and fast food restaurant density within Harris County
A) Map illustrates gestational diabetes prevalence in zip code areas of Harris County B) Map reveals fast food restaurant density (per 100,000 inhabitants) in different zip code areas of Harris County, assembled by ArcGIS 10.3 Desktop Advanced
Figure 2
Figure 2. Correlation of HbA1c levels with fast food restaurant density
Scatterplot showing the correlation of HbA1c levels with fast-food restaurant density (Spearman’s Rank r=0.290, p=0.009).
See this image and copyright information in PMC

Comment in

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